Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Feature-level medical image fusion method based on 3D (three dimension) shearlet transform

A medical image and fusion method technology, applied in the field of medical image processing and application, can solve the problems of adverse effects of medical diagnosis, low sparse representation ability of fusion image quality, and easily ignored information.

Active Publication Date: 2014-08-13
UNIV OF ELECTRONIC SCI & TECH OF CHINA
View PDF1 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In view of the above-mentioned prior art, the purpose of the present invention is to provide a feature-level medical image fusion method based on 3D shearlet transform, which solves the problem of the fusion method based on wavelet transform and pyramid transform. The quality of the fused image is relatively low due to the representation ability; as well as the defect that locally important but insignificant information is easily ignored during image fusion, and these defects will eventually have an adverse effect on medical diagnosis

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Feature-level medical image fusion method based on 3D (three dimension) shearlet transform
  • Feature-level medical image fusion method based on 3D (three dimension) shearlet transform
  • Feature-level medical image fusion method based on 3D (three dimension) shearlet transform

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0067] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0068] Taking T2* magnitude image and QSM image as an example, this experiment uses the method of the present invention to process the three-dimensional T2* magnitude image and QSM image, and finally obtains a fusion image. In the example, the size of the image is 128×128×128.

[0069] The image fusion method of this embodiment first considers how to represent the anisotropy of the three-dimensional image, and the shear transform can well represent the anisotropic characteristics of the image; secondly, considering the influence of the translational change properties brought about by the DWT transform, a dual-tree complex wavelet transform is performed (DTCWT); Finally, it is considered to fuse as much information as possible into the fusion coefficient image with the low-frequency coefficients and high-frequency coefficients: for low-frequency ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a feature-level medical image fusion method based on 3D (three dimension) shearlet transform, belonging to the technical field of medical image processing and application. The feature-level medical image fusion method mainly comprises the following steps: 1, performing 3D-D-CSST (three dimensional-discrete-compact shearlet transform) or 3D-DT-CSST (three dimensional dual-tree compact shearlet transform) on two images to obtain transformation coefficient images Ca and Cb; 2, performing image fusion on transformation coefficients to obtain a fusion coefficient Cf; and 3, performing DWT or DTCWT inverse transformation, performing backward shear transformation on the transformed image to obtain a fusion image Vf. According to the feature-level medical image fusion method, the problems that the quality of a fused image is relatively low and information which is partially important and is not remarkable is easily ignored are solved.

Description

technical field [0001] The invention belongs to the technical field of medical image processing and application, and specifically relates to a feature-level medical image fusion method based on 3D shearlet transform, which solves the problem that the quality of the fused image is relatively low and locally important but insignificant information is easily overlooked . Background technique [0002] Medical image fusion is a kind of image fusion, and many methods have been widely used in clinical diagnosis. Fusion refers to the process of extracting and merging important information about the target from source images collected by different devices such as CT and MRI into one image. The information contained in images generated by different devices or different configurations of the same device is different, some information is similar, but most of the information is complementary. For example, CT images mainly provide information on dense and hard tissues of the human body,...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06T5/50G06T3/40A61B6/03A61B5/055
Inventor 王帅段昶刘想程建
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com